Data Stories podcast: Episode 37, teaching visualisation

As ever it was a privilege to be invited to take part in the latest episode 37 of the Data Stories podcast. I joined Enrico and Moritz alongside Scott Murray to discuss the challenges of learning and teaching data visualisation.

Many thanks again to Enrico and Moritz for inviting me on the show for a fifth time!

Tasty visualisations from the Barcelona Data Cuisine

Data Cuisine is an experimental workshop investigating the creative possibilities at the intersection between food and data: “exploring food as a medium for data expression”. Between 10th and 13th of June, Moritz Stefaner, a man who needs no introduction, along with Dr Susanne Jaschko and chef Sebastian Velilla ran the second edition of the workshop in Barcelona (the first was in Helsinki in 2012) part of the Big Bang Data exhibition at CCCB, and in coordination with Sónar.

The focus of the experiment is to research creative ways to represent local open data in through the inherent qualities of food like color, form, texture, smell, taste, nutrition, origin etc. It is a truly multi-sensory approach to encoding data, something that I’ve highlightedpreviously as been a really interesting branch of the visualisation field.

The workshop is a collaborative research experience, blurring the boundaries between teachers and participants, data and food. At its end, an local data menu is created and publicly tasted.

Moritz and Susanne have just finished writing up details and publishing photos of the dishes made during this Barcelona workshop. Probably a good idea to not visit the site with an empty stomach.

Based on an innovative interactive map-timeline the visualisation elegantly comprises a main map element that shows the bigger-picture view of the places you have visited with a series of sequenced circular map snippets that encode when and how long you have stayed in each location. You also then have the option to upload photos from Flickr to supplement the map-timeline with a visual slideshow story of your journey that can be shared with friends and family – and even complete strangers, should you wish.

You can learn more about the project here and, of course, the authors are keen to invite anyone to create their own ‘visit’ story.

Guest post: Using Mode to re-engineer data visualisations

Occasionally I invite folks to contribute guest posts to profile their work, ideas or knowledge. This guest post comes from Benn Stancil from a startup called Mode who have created a really interesting tool that allows you to reverse engineer analysis/visualisations in order to potentially take them in new directions. The product was opened to the public yesterday, so you can check it out and a few examples of the visualisations that people have built with it.

Can we learn from and build on each other’s visualizations?

Like so many others, I’ve long been fascinated by learning from data–and as a result, been an avid consumer of data visualizations. The explosion of data in recent years has fueled a similar explosion of beautiful and insightful visualizations, created by everyone from industry leaders like the New York Times and Guardian to undiscovered brilliance hidden in obscure corners of the internet.

Even the best visualizations, however, rarely answer all of a viewer’s questions. We often want to understand how the data was collected, how it would look if considered from a different angle, what story it would tell if combined with other data, or how the visualization was built. In other words, great visualizations not only answer questions, but inspire more.

Unfortunately, it’s often difficult to document and share enough information to answer these follow-up questions. Creators carry the burden of sharing their data sources, their analysis that aggregated and combined data, their visualization code, and many other details. And piecing this information together after the fact is equally burdensome for consumers. The bit of knowledge someone new could add by remixing the analysis–or the bit they could learn by better understanding the original–often hits a dead-end, no matter how inspiring the visualization.

Introducing Mode

In part because of my own personal frustration, I recently cofounded a company, called Mode, aimed at providing solutions to these challenges. Mode’s mission is to connect data and the people who analyze and visualize it. We’ve built a web-based tool that executes analysis, displays results, and renders fully custom visualizations all in one place. By saving, versioning, and packaging the entire workflow together, anyone who discovers the analysis can immediately click through the results to see the underlying data, the analysis, and how the visualization was created. Right now, we’re focused on supporting SQL for analysis and web languages (HTML, CSS, and Javascript) for visualizations, though we’re planning to adding R- and Python-based tools soon.

The above is a screenshot of a finished visualization. You can see the query, visualization code, and previous versions by clicking on the Query, Presentation, and Run History tabs above the graphic.

By organizing all of this information together in a simple package, people can immediately understand and add to visualizations without having to rebuild the work themselves. We’ve made this possible in one click–simply click clone on the screen above, and you’ll be working with with same visualization published by the original author, exactly where they left off.

When a piece of work is cloned, the original author not only maintains credit, but also sees who cloned their work and what they’re doing with it. This allows the community to push an analysis forward, without ever losing sight of the creator and without the creator losing sight of how their work is evolving.

Others can then working with the analysis and visualization in their own workspaces. They can even add their own data–Mode allows multiple creators’ data to be combined in a single visualization. Because all of this work happens in the browser, Mode doesn’t require setting up a development environment or finding a place to host the visualization.

Here is a screenshot of the presentation editor, where you can add custom visualization code and preview it.

Finally, we want people to be able to easily share their work. All visualizations in Mode can be shared via URL, or can be embedded anywhere on the internet, just like a YouTube video. The embedded visualizations, like the one below, can be fully interactive, and link back to all of the data and work.

We Want Your Advice

Our approach to making data visualizations more accessible is largely influenced by our own experiences as data analysts. Surely others, who have had different experiences and objectives, face other challenges or have other ideas for solutions.

We’d love to hear what you think of our direction and how we can tailor it to your needs. What problems have you had when collaborating on data visualizations? What are your biggest struggles, and how would you solve them? If you’d like to check out our approach, Mode is free to use and you can sign up here.

We’re looking forward to see what great work people can build with Mode – and perhaps more importantly, what we can learn from each other. The world is producing fascinating data at an unprecedented pace, on subjects ranging from air quality in Chicago, to taxi traffic in Seattle, to the tattoo trends in the NBA. Great technologies for producing visualizations, like D3, Raphaël, and R, are constantly improving. And we have many giants in the data visualization community to look up to. At Mode, our hope is to help all of us stand on their shoulders.

Beginning the journey towards book number two

A quick announcement to the broader visitorship out there, having briefly tweeted about it last week I am thrilled to have received approval to start work on my second book, which will be published by SAGE (one of the “world’s leading independent academic and professional publisher”, I’ll have you know).

I’m not going to share any details on the title or contents just yet but, as with all my endeavours, it will be aimed at covering in detail the practical craft of data visualisation (it won’t be a glossy coffee-table gallery of different works, for example) with a realistic target completion date being the latter part of 2015.

One of the main things that excites me about this project is that the publishers have stated their commitment to explore some great innovations in the relationship between print and digital form: not just in replicating a text digitally but about creating a digital companion to the printed content. I think that is needed in discussing this subject.

The second main thing that excites me is that the book WILL be printed in colour. Obvious, right? Well, not always, sadly…

My experiences from writing the first book were that it is a painful slog, fraught with mental blocks, anxieties about added-value, fears of mis-quoting or mis-referencing ideas, frustrations at trying to secure permissions for image usage etc. I think this quote astutely sums up the prospect:

Whilst I was satisfied with the content of my first book (not so much it’s form), I feel I have moved on considerably with so much more to say than I had the chance to share back then. I’m confident that, with the professional support SAGE will unquestionably provide me, this second title will truly be the book I have wanted to produce. I’ll keep you posted on progress…

Best of the visualisation web… April 2014

At the end of each month I pull together a collection of links to some of the most relevant, interesting or thought-provoking web content I’ve come across during the previous month. Here’s the latest collection from April 2014.

Visualisations/Infographics

Includes static and interactive visualisation examples, infographics and galleries/collections of relevant imagery.

Economist | A new form of interactive static visualisation: representing the odds of being murdered in 5 countries via the chance of a dart hitting the same display. We clearly now must see more dart vis, this needs to be a thing.

Jonathan Hull | Jonathan uses the periodic table framework to good effect, visualising the abundance of elements in the universe, ocean, earth etc.

Washington Post | ‘The depth of the problem’ possibly my first liked tower graphic as it perfectly captures the ludicrous depth of the search for the Malaysian airliner’s black box

The Why Axis | ‘Today we have better access to health information than ever before but this means little without greater understanding. Visualizing Health is a weapon in the fight to create a culture of health.’

Subject News

Includes announcements within the field, brand new sites, new (to me) sites, new books and generally interesting developments.

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